A series of studies investigate model complexity measures that can explain generalization capability of deep learning models [1]}, [2]}, [3]}, [4]}.
Neyshabur et al. [1]} suggests that, from the perspective of generalization, a complexity measure should satisfy the following property: a learned model with lower complexity generalizes better.
In particular, they list several requirements which are summarized from observed empirical phenomena and are expected to be satisfied by complexity measures.
